Complete your mastery of statistics. Get an advanced understanding of concepts such as t-distribution, degrees of freedom, chi-square testing, regression testing, and ANOVA.
- Statistics are everywhere. The world is taking notice. It doesn't matter what industry you're in. It doesn't matter what your passions and hobbies include. Nearly everyone is using statistics to discover, improve and predict. Welcome to Statistics Fundamentals Three. If you've come this far, you're obviously a person that respects, appreciates, and perhaps loves statistics and you know there's more. You see the limitations in the basic statistics tools.
You wonder how to know if any specific factors are influencing the results and may you wonder what all this discussion about regression analysis is all about. My name is Eddie Davila and I'm a university instructor with degrees in business and engineering. I write e-books and of course, I develop online educational content. I'm a huge sports fan. I love to follow the entertainment industry and I'm passionate about science and health and I can tell you that in every important facet of my life, having a better understanding of statistics allows me to improve my performance and often to find a greater level of satisfaction whether I'm working or playing.
This course, Statistics Fundamentals Part Three is the final installment in our three-part series. In this course, we'll look at the special case of small sample sizes. We'll compare two populations. I'll introduce you to the world of regression analysis and add to our statistics alphabet soup by talking about t-statistics, f-statistics, R squared. I'll share things that may sound intimidating but really aren't that scary.
Things like degrees of freedom, Chi-Square and ANOVA. Along the way, you'll discover more of the wonderfully intricate layers of statistics. So, welcome to Statistics Fundamentals Part Three.
- Working with small sample sizes
- Using t-statistic vs. z-statistic
- Calculating confidence intervals with t-scores
- Comparing two populations (proportions)
- Comparing two population means
- Chi-square testing
- ANOVA testing
- Regression testing